Just when you thought nothing could be as disruptive as the switch to “mobile first” design, a sea change is occurring in what’s expected and even in what’s possible with UX design. Here are some of the most important developments, from both a basic design standpoint and from under the hood:

Just say, “no”: the stock photo backlash

While the sheer volume and quality of stock imagery available to marketers has increased dramatically over the past decade, its use has only sensitized consumers to spotting them as such, immediately. It used to be that consumers had no idea the stock photo business existed, but today it’s so well known, there are stock photo memes all over social media (https://www.facebook.com/sophisticatedstockphotomemes/). It probably doesn’t help that an incredible percentage of stock photos used across the web feature the same model. (http://asianstockphotogirl.tumblr.com/). Combine that with the near standardization of page structures stemming from the increase in responsive design, and we are seeing that marketers are finding it difficult to differentiate their online experiences. So what’s a marketer to do? Given that no one should return to unresponsive design, to truly differentiate, what remains is the need to invest in original imagery. Despite the added investment of time, energy, and funds required to concept, execute, and deploy original photography and illustrations, the long-term benefits of differentiation and perceived authenticity should be a net positive for marketers.

Let it bleed: images/video without borders

It is no coincidence that as the majority of users are now accessing the web through mobile devices with high-speed mobile broadband, we are seeing an influx of full bleed imagery and video in website headers. Subjectively, the technique feels more immersive. Objectively, it is a more efficient use of real estate on smaller mobile screens. Further, on larger desktop displays, sites feel more cinematic. Either way, the design pattern is becoming as common, and frankly, as expected as hamburger menus and social icons.

When the UX touches you back: haptic feedback

Used in video game controllers for nearly two decades, haptic feedback is the use of vibration to mimic interaction with real-world objects or environments or to provide silent/private feedback to users. Apple’s latest MacBook laptops quite convincingly substituted a physically clicking trackpad button for a nonmoving, pressure-sensitive pad that uses vibration and sound to simulate the traditional click. Now imagine you’re shopping on your mobile device, running your finger along your mobile screen, and “feeling” the texture of woven fabric or the grain of leather. Now imagine navigating a complex series of buttons on your mobile screen by feel alone. Haptic feedback could let you “feel” the edge of a button as you slide your finger, just as if it were physically raised from the surface.

Not intended for all audiences: Age responsive design

Until recently, responsive design referred mainly to changing, compressing, or expanding visual design elements to provide a more suitable experience based on the user’s device of the moment. But as we are increasingly seeing personalized content experiences, there is a burgeoning movement to make user experiences responsive to age as well as device. That can mean altering reading levels, type size, imagery, color scheme, navigation elements, and editorial content, even advertiser profile, in an age-appropriate fashion.

Rent-a-brain: cloud-based AI

First we saw the advent of big data. Then, unsurprisingly, we saw the big data hangover as companies struggled to generate useful insights that could lead to truly predictive behavioral models. Thankfully, recent advances in machine learning have turned what was an arduous analytical and computational challenge into something fully automated and optimized. The downside? Computing infrastructure that is capable of using machine learning to process massive data sets can be massively expensive to install and maintain. The solution? The cloud. Companies such as IBM and Amazon are now offering machine learning as a pay-as-you-go service. That means predictive analytics can potentially drive the user experience for all but the smallest of enterprises.

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